PROJECT SUMMARY/ABSTRACT In response to PAR-18-062: Accelerating the Pace of Drug Abuse Research Using Existing Data, this competing renewal ?Trajectories of Nonmedical Prescription Drug Misuse? builds on our parent R01 and proposes to use national data to assess the longitudinal relationships among trajectories of medical and nonmedical use of prescription medications, functional outcomes and adverse consequences from adolescence (age 18) to middle adulthood (age 50). The proposed research will focus on prescription opioids, sedatives/tranquilizers, and stimulants because the medical and nonmedical use of these medications and related consequences have increased over the past three decades in the U.S. To date, no national studies have examined the impact of attrition on medical and nonmedical use estimates in longitudinal studies. Moreover, national studies fail to examine long-term functional outcomes or adverse outcomes associated with different trajectories of medical and nonmedical use of prescription medications. More longitudinal studies of adolescents followed into middle adulthood are needed because adults are more likely to be prescribed scheduled medications and often assume greater life/work responsibilities. As a result, we propose secondary analyses focusing primarily on the MTF longitudinal panel sample, which features 11 separate cohorts of approximately 26,400 high school seniors (modal age 18) who were followed 1-2 years (ages 19-20), 3-4 years (ages 21-22), 5-6 years (ages 23-24), 7-8 years (ages 25-26), 9-10 years (ages 27-28), 11-12 years (ages 29- 30), 17 years (age 35), 22 years (age 40), 27 years (age 45), and 32 years later (age 50) resulting in 11 overall waves of data. The MTF data provide a unique opportunity with sufficient measures and sample sizes for examining relationships over 32 years and to meet the objectives of our study, which aims to: 1) estimate the bias in estimated rates of medical and nonmedical use of prescription opioids, sedatives/tranquilizers, and stimulants at different developmental periods and in estimated rates of change over time in medical and nonmedical use due to differential attrition, by comparing and evaluating alternative weighting and imputation approaches; 2) identify the trajectories of medical and nonmedical use of prescription opioids, sedatives/tranquilizers, and stimulants based on multiple waves of longitudinal data from adolescence (age 18) to middle adulthood (age 50); 3) use growth mixture modeling to evaluate whether subject-specific trajectories of nonmedical and medical use of prescription opioids, sedatives/tranquilizers, and stimulants from adolescence to age 45 are predictive of functional outcomes (e.g., educational attainment) and adverse consequences (e.g., SUD symptoms) at age 50; and 4) examine the adolescent risk and protective factors for trajectories of medical and nonmedical use of prescription medications that are associated with poor functional outcomes and adverse consequences in middle adulthood using a theory-based developmental model.